The novel technique is based on the VarifocalNet deep-learning object detection framework, which was reportedly tweaked to achieve quicker and more accurate results. Compared to other such methods, ...

Researchers have tested eight stand-alone deep learning methods for PV cell fault detection and have found that their accuracy was as high as 73%. All methods were trained and tested on the ELPV ...

In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...

This new technical paper titled “End-to-end deep learning framework for printed circuit board manufacturing defect classification” is from researchers at École de technologie supérieure (ÉTS) in ...

Defect detection requirements on the order of 10 defective parts per million (DPPM) are driving improvements in inspection tools’ resolution and throughput at foundries and OSATs. However, defects ...

On the technology spectrum, railroads would certainly seem to skew toward the brutally simplistic side of things. A couple of strips of steel, some wooden ties and gravel ballast to keep everything in ...

Defect inspection scientists from Huazhong University of Science and Technology, Harbin Institute of Technology and The Chinese University of Hong Kong make a thorough review of new perspectives and ...